Proving Linearity of Transformation: f as a Real Number

In summary, the conversation discusses proving that T(p) is a linear transformation from P2 to F, where f is treated similarly to a real number. The properties of a linear transformation are shown to hold, completing the proof.
  • #1
bifodus
10
0
Let f: R --> R and let T: P2 --> F, and T(p) = p(f). Prove that T is a linear transformation.

P2 is the set of polynomials of degree 2 or less, and F is the set of all functions.

It seems to me that I can treat f as really just a real number, in which case it's no different from proving T(p) = p(x) for all x in R. Is it this simple?

Thanks
 
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  • #2
You can treat f similarly to a real number, because you can add and multiply real-valued functions, but you can't treat it as a real number.

Secondly, you're not trying to prove T(p) = p(f): that's the definition of T. You're trying to prove that T is a linear transformation from P2 to F.

Finally, F is is not just a set, it's a vector space.
 
  • #3
To prove that T(p) is a linear transformation, you must show that it has the properties of a linear transformation, that is:
(a) T(a+b)=T(a)+T(b) for a,b in P2
(b) T(ca)=cT(a) for a in P2 and c in R
 
  • #4
So let p1 and p2 be elements of P2
Then T(p1 + p2) = (p1 + p2)(f) = p1(f) + p2(f) = T(p1) + T(p2)
and T(cp1) = cp1(f) = cT(p1)

Is this sufficient to show that T is a linear transformation or am I leaving something out?
 
  • #5
That looks right. Good job!
 

Related to Proving Linearity of Transformation: f as a Real Number

1. What is a linear transformation?

A linear transformation is a mathematical function that maps vectors from one vector space to another in a way that preserves the linear structure of the original space.

2. How do you prove that a transformation is linear?

To prove that a transformation is linear, you must show that it satisfies two conditions: additivity and homogeneity. Additivity means that the transformation of the sum of two vectors is equal to the sum of the individual transformations, while homogeneity means that the transformation of a scalar multiple of a vector is equal to the scalar multiple of the transformation of the original vector.

3. What is the difference between a linear transformation and a non-linear transformation?

A linear transformation preserves the linear structure of a vector space, while a non-linear transformation does not. This means that a linear transformation will always produce a straight line when graphed, while a non-linear transformation can produce curves or other shapes.

4. How do you write a linear transformation in matrix form?

A linear transformation can be represented in matrix form by writing the coefficients of the transformation as entries in a matrix. The columns of the matrix will correspond to the transformed basis vectors of the original vector space.

5. How are linear transformations used in real-world applications?

Linear transformations are used in a variety of fields, including physics, engineering, and computer graphics. They can be used to model physical systems, analyze data, and create computer-generated images. In particular, they are useful for representing and manipulating geometric objects and transformations.

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